Subject Datasheet

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Budapest University of Technology and Economics
Faculty of Transportation Engineering and Vehicle Engineering
1. Subject name Digital Image Processing
2. Subject name in Hungarian Képfeldolgozás
3. Code BMEKOALD002 4. Evaluation type exam grade 5. Credits 4
6. Weekly contact hours 2 (0) Lecture 2 (0) Practice 0 (0) Lab
7. Curriculum
PhD Programme
8. Role
Basic course
9. Working hours for fulfilling the requirements of the subject 120
Contact hours 56 Preparation for seminars 12 Homework 15
Reading written materials 5 Midterm preparation 12 Exam preparation 20
10. Department Department of Material Handling and Logistics Systems
11. Responsible lecturer Dr. Szirányi Tamás
12. Lecturers Dr. Szirányi Tamás, Rózsa Zoltán
13. Prerequisites  
14. Description of lectures
The aim of the course is to give students the opportunity to discover novel laws in one of the following topics: computer analysis, correction and processing of two- and three-dimensional images and videos; recognition and classification of figurative shapes; mathematical methods of image processing and evaluation, manipulation.
15. Description of practices
During the computer practice the students are programming and solving examples about the topic of the lectures.
16. Description of labortory practices
17. Learning outcomes
A. Knowledge
  • Knowing the processes and basic elements of image processing, enhancement and manipulation.
  • Having comprehensive knowledge about the different topics of image acquisition.
  • Knowing the computer description of images and basic properties.
  • Knowing the basics of shape recognition.
  • Knowing the basic properties of human vision.
  • Knowing the principles of decision making.
  • Having comprehensive about convolution and application areas.
  • Knowing the methods of motion-analysis and tracking.
  • Knowing the basic methods of texture characterization.
B. Skills
  • Being able to apply the knowledge in tasks related to image processing, enhancement and manipulation.
  • Application of decision making methods.
  • Being able to apply of different shape recognition algorithms.
  • Being able to solve tracking and motion analysis problems.
  • Being able to solve the problems alone or in group and efficiently transfer the knowledge. 
  • Having original/innovative ideas.
C. Attitudes Working efficiently alone and in group. Seeking for relations to other subjects. Being open to use mathematical and informatic tools.Seeking to know and learn the neccesary tools.
D. Autonomy and Responsibility
  • Seeking to solve the problems accurately and error-free.
  • Finding solutions alone.
  • Taking into considereations the effects of the decisions. 
  • Applying systematic approach.
18. Requirements, way to determine a grade (obtain a signature)
The evaluation of the learning results is based on the written (homework) and oral (oral exam) performance.
19. Opportunity for repeat/retake and delayed completion
The homework can be corrected until the end of the week of examinations.
The oral exam can be re-take first free of charge. The second and higher re-take of the same subject has charge regulated by the university.
20. Learning materials
Online notes provided by the department; Bernd Jahne: Digital Image Processing, 5st edition, Springer, Heidelberg, 2002; W. K. Pratt: Digital Image Processing, Wiley, 2001.; Kató Zoltán, Czúni László: Számítógépes látás, Typotex, 2011
Effective date 27 November 2019 This Subject Datasheet is valid for Inactive courses